Method and system for verifying interval multi-attribute intelligent analysis experiment

The invention relates to the technical field of information processing, and particularly discloses an interval multi-attribute intelligent analysis experimental verification method and system, and the method comprises the steps: S1, inputting experimental verification according to the characteristics of the experimental verification and an interval multi-attribute algorithm, S2, deploying a nanodet deep learning neural network system in a server, S3, preparing a data set, S4, training, and S5, verifying. Through a more complex and more flexible mathematical model and an advanced optimization algorithm, the performance of the model can be improved, the model can better fit data, and more comprehensive experimental evaluation, including cross validation on different data subsets, model comparison, optimization of different hyper-parameters and the like, is generally needed when a new method is introduced. The method is advantaged in that the model behavior can be better understood, the data volume supported by